NDLI: Investigation on Different Kernel Functions for Weighted Kernel Regression in Solving Small Sample Problems

Content Provider	IEEE Xplore Digital Library
Author	Shapiai, M.I. Sudin, S. Ibrahim, Z. Khalid, M.
Copyright Year	2011
Abstract	Previously, weighted kernel regression (WKR) has proved to solve small problems. The existing WKR has been successfully solved rational functions with very few samples. The design and development of WKR is important in order to extend the capability of the technique with various kernel functions. Based on WKR, a simple iteration technique is employed to estimate the weight parameters with Gaussian as a kernel function before WKR can be used in predicting the unseen test samples. In this paper, however, we investigate various kernel functions with Particle Swarm Optimization (PSO) as weight estimators as it offers such flexibility in defining the objective function. Hence, PSO has the capability to solve non-closed form solution problem as we also introduce regularization term with L1 norm in defining the objective function as to solve training sample, which corrupted by noise. Through a number of computational experiments, the investigation results show that the prediction quality of WKR is primarily dominated by the smoothing parameter selection rather than the type of kernel function.
Starting Page	64
Ending Page	69
File Size	453367
Page Count	6
File Format	PDF
ISBN	9781467300605
DOI	10.1109/EMS.2011.39
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-11-16
Publisher Place	Spain
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training kernel functions Smoothing methods Shape Search problems Mathematical model particle swarm optimization (PSO) Kernel Equations small samples Weighted kernel regression (WKR)
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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